Usefulness of Computerized Method for Lung Nodule Detection in Digital Chest Radiographs Using Temporal Subtraction Images
Rationale and Objectives The aim of this study was to evaluate the usefulness of a novel computerized method for lung nodule detection on digital chest radiographs using temporal subtraction images. Materials and Methods To significantly reduce the number of false-positive results while maintaining...
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| Veröffentlicht in: | Academic radiology 2011-08, Vol.18 (8), p.1000-1005 |
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| container_title | Academic radiology |
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| creator | Aoki, Takatoshi, MD Oda, Nobuhiro, PhD Yamashita, Yoshiko, MD Yamamoto, Keiji, PhD Korogi, Yukunori, MD |
| description | Rationale and Objectives The aim of this study was to evaluate the usefulness of a novel computerized method for lung nodule detection on digital chest radiographs using temporal subtraction images. Materials and Methods To significantly reduce the number of false-positive results while maintaining high sensitivity, temporal subtraction images, which can enhance interval changes on sequential chest radiographs, were used. Fifty-one cases with lung nodules |
| doi_str_mv | 10.1016/j.acra.2011.04.008 |
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Materials and Methods To significantly reduce the number of false-positive results while maintaining high sensitivity, temporal subtraction images, which can enhance interval changes on sequential chest radiographs, were used. Fifty-one cases with lung nodules <3 cm and 51 cases without lung nodules were selected for an observer performance test. Twelve radiologists participated in this observer performance test. The radiologists’ performance was evaluated using receiver-operating characteristic analysis, on a continuous rating scale. To estimate the numbers of cases affected beneficially and those affected detrimentally using this computerized method, the computer output was assumed to have an effect on an observer’s diagnosis when there was a difference in rating score of ≥30% between the first and second ratings. Results The average area under the curve for all radiologists increased significantly from 0.849 to 0.950 with the computerized method ( P < .001). The mean number of cases affected beneficially was significantly higher than that of cases affected detrimentally (8.92 vs 1.25, P < .001). Conclusions The novel computerized method using temporal subtraction images would be useful in detecting lung nodules on digital chest radiographs.</description><identifier>ISSN: 1076-6332</identifier><identifier>EISSN: 1878-4046</identifier><identifier>DOI: 10.1016/j.acra.2011.04.008</identifier><identifier>PMID: 21718956</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; Analysis of Variance ; chest radiograph ; Clinical Competence ; computer-aided-diagnosis ; Diagnosis, Computer-Assisted - methods ; False Positive Reactions ; Female ; Humans ; lung cancer ; Lung Neoplasms - diagnostic imaging ; Lung nodule ; Male ; Radiographic Image Enhancement - methods ; Radiography, Thoracic - methods ; Radiology ; ROC Curve ; Sensitivity and Specificity ; Subtraction Technique</subject><ispartof>Academic radiology, 2011-08, Vol.18 (8), p.1000-1005</ispartof><rights>AUR</rights><rights>2011 AUR</rights><rights>Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c410t-5e06f3f1ef77c60a67b0795558d4477626abd13f2b3d44b721c9a19ddfe239ba3</citedby><cites>FETCH-LOGICAL-c410t-5e06f3f1ef77c60a67b0795558d4477626abd13f2b3d44b721c9a19ddfe239ba3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.acra.2011.04.008$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21718956$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Aoki, Takatoshi, MD</creatorcontrib><creatorcontrib>Oda, Nobuhiro, PhD</creatorcontrib><creatorcontrib>Yamashita, Yoshiko, MD</creatorcontrib><creatorcontrib>Yamamoto, Keiji, PhD</creatorcontrib><creatorcontrib>Korogi, Yukunori, MD</creatorcontrib><title>Usefulness of Computerized Method for Lung Nodule Detection in Digital Chest Radiographs Using Temporal Subtraction Images</title><title>Academic radiology</title><addtitle>Acad Radiol</addtitle><description>Rationale and Objectives The aim of this study was to evaluate the usefulness of a novel computerized method for lung nodule detection on digital chest radiographs using temporal subtraction images. Materials and Methods To significantly reduce the number of false-positive results while maintaining high sensitivity, temporal subtraction images, which can enhance interval changes on sequential chest radiographs, were used. Fifty-one cases with lung nodules <3 cm and 51 cases without lung nodules were selected for an observer performance test. Twelve radiologists participated in this observer performance test. The radiologists’ performance was evaluated using receiver-operating characteristic analysis, on a continuous rating scale. To estimate the numbers of cases affected beneficially and those affected detrimentally using this computerized method, the computer output was assumed to have an effect on an observer’s diagnosis when there was a difference in rating score of ≥30% between the first and second ratings. Results The average area under the curve for all radiologists increased significantly from 0.849 to 0.950 with the computerized method ( P < .001). The mean number of cases affected beneficially was significantly higher than that of cases affected detrimentally (8.92 vs 1.25, P < .001). Conclusions The novel computerized method using temporal subtraction images would be useful in detecting lung nodules on digital chest radiographs.</description><subject>Aged</subject><subject>Analysis of Variance</subject><subject>chest radiograph</subject><subject>Clinical Competence</subject><subject>computer-aided-diagnosis</subject><subject>Diagnosis, Computer-Assisted - methods</subject><subject>False Positive Reactions</subject><subject>Female</subject><subject>Humans</subject><subject>lung cancer</subject><subject>Lung Neoplasms - diagnostic imaging</subject><subject>Lung nodule</subject><subject>Male</subject><subject>Radiographic Image Enhancement - methods</subject><subject>Radiography, Thoracic - methods</subject><subject>Radiology</subject><subject>ROC Curve</subject><subject>Sensitivity and Specificity</subject><subject>Subtraction Technique</subject><issn>1076-6332</issn><issn>1878-4046</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kcFu1DAURSMEoqXwAyyQd6wSnh3HTiSEhKbQVhpAop215dgvMx6SONgJUvv1OJrCggUrW9a5V37nZdlrCgUFKt4dC22CLhhQWgAvAOon2TmtZZ1z4OJpuoMUuShLdpa9iPEIQCtRl8-zM0YlrZtKnGcPu4jd0o8YI_Ed2fhhWmYM7gEt-YLzwVvS-UC2y7gnX71deiSXOKOZnR-JG8ml27tZ92RzwDiT79o6vw96OkSyiy5l7nCYfEjA7dLOQZ9yN4PeY3yZPet0H_HV43mR7T5_uttc59tvVzebj9vccApzXiGIruwodlIaAVrIFmRTVVVtOZdSMKFbS8uOtWV6aCWjptG0sbZDVjatLi-yt6feKfifS_qmGlw02Pd6RL9EVUvO64pySCQ7kSb4GAN2agpu0OFeUVCrcnVUq3K1KlfAVVKeQm8e65d2QPs38sdxAt6fAExD_nIYVDQOR4PWhSRSWe_-3__hn7jp3eiM7n_gPcajX8KY9CmqIlOgbtelrzunFICBrMvfwxSoaw</recordid><startdate>20110801</startdate><enddate>20110801</enddate><creator>Aoki, Takatoshi, MD</creator><creator>Oda, Nobuhiro, PhD</creator><creator>Yamashita, Yoshiko, MD</creator><creator>Yamamoto, Keiji, PhD</creator><creator>Korogi, Yukunori, MD</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20110801</creationdate><title>Usefulness of Computerized Method for Lung Nodule Detection in Digital Chest Radiographs Using Temporal Subtraction Images</title><author>Aoki, Takatoshi, MD ; Oda, Nobuhiro, PhD ; Yamashita, Yoshiko, MD ; Yamamoto, Keiji, PhD ; Korogi, Yukunori, MD</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c410t-5e06f3f1ef77c60a67b0795558d4477626abd13f2b3d44b721c9a19ddfe239ba3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Aged</topic><topic>Analysis of Variance</topic><topic>chest radiograph</topic><topic>Clinical Competence</topic><topic>computer-aided-diagnosis</topic><topic>Diagnosis, Computer-Assisted - methods</topic><topic>False Positive Reactions</topic><topic>Female</topic><topic>Humans</topic><topic>lung cancer</topic><topic>Lung Neoplasms - diagnostic imaging</topic><topic>Lung nodule</topic><topic>Male</topic><topic>Radiographic Image Enhancement - methods</topic><topic>Radiography, Thoracic - methods</topic><topic>Radiology</topic><topic>ROC Curve</topic><topic>Sensitivity and Specificity</topic><topic>Subtraction Technique</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aoki, Takatoshi, MD</creatorcontrib><creatorcontrib>Oda, Nobuhiro, PhD</creatorcontrib><creatorcontrib>Yamashita, Yoshiko, MD</creatorcontrib><creatorcontrib>Yamamoto, Keiji, PhD</creatorcontrib><creatorcontrib>Korogi, Yukunori, MD</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Academic radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aoki, Takatoshi, MD</au><au>Oda, Nobuhiro, PhD</au><au>Yamashita, Yoshiko, MD</au><au>Yamamoto, Keiji, PhD</au><au>Korogi, Yukunori, MD</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Usefulness of Computerized Method for Lung Nodule Detection in Digital Chest Radiographs Using Temporal Subtraction Images</atitle><jtitle>Academic radiology</jtitle><addtitle>Acad Radiol</addtitle><date>2011-08-01</date><risdate>2011</risdate><volume>18</volume><issue>8</issue><spage>1000</spage><epage>1005</epage><pages>1000-1005</pages><issn>1076-6332</issn><eissn>1878-4046</eissn><abstract>Rationale and Objectives The aim of this study was to evaluate the usefulness of a novel computerized method for lung nodule detection on digital chest radiographs using temporal subtraction images. Materials and Methods To significantly reduce the number of false-positive results while maintaining high sensitivity, temporal subtraction images, which can enhance interval changes on sequential chest radiographs, were used. Fifty-one cases with lung nodules <3 cm and 51 cases without lung nodules were selected for an observer performance test. Twelve radiologists participated in this observer performance test. The radiologists’ performance was evaluated using receiver-operating characteristic analysis, on a continuous rating scale. To estimate the numbers of cases affected beneficially and those affected detrimentally using this computerized method, the computer output was assumed to have an effect on an observer’s diagnosis when there was a difference in rating score of ≥30% between the first and second ratings. Results The average area under the curve for all radiologists increased significantly from 0.849 to 0.950 with the computerized method ( P < .001). The mean number of cases affected beneficially was significantly higher than that of cases affected detrimentally (8.92 vs 1.25, P < .001). Conclusions The novel computerized method using temporal subtraction images would be useful in detecting lung nodules on digital chest radiographs.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>21718956</pmid><doi>10.1016/j.acra.2011.04.008</doi><tpages>6</tpages></addata></record> |
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| subjects | Aged Analysis of Variance chest radiograph Clinical Competence computer-aided-diagnosis Diagnosis, Computer-Assisted - methods False Positive Reactions Female Humans lung cancer Lung Neoplasms - diagnostic imaging Lung nodule Male Radiographic Image Enhancement - methods Radiography, Thoracic - methods Radiology ROC Curve Sensitivity and Specificity Subtraction Technique |
| title | Usefulness of Computerized Method for Lung Nodule Detection in Digital Chest Radiographs Using Temporal Subtraction Images |
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